Multiperspective Focus+Context Visualization

Abstract

Occlusions are a severe bottleneck for the visualization of large and complex datasets. Conventional images only show dataset elements to which there is a direct line of sight, which significantly limits the information bandwidth of the visualization. Multiperspective visualization is a powerful approach for alleviating occlusions to show more than what is visible from a single viewpoint. However, constructing and rendering multiperspective visualizations is challenging. We present a framework for designing multiperspective focus+context visualizations with great flexibility by manipulating the underlying camera model. The focus region viewpoint is adapted to alleviate occlusions. The framework supports multiperspective visualization in three scenarios. In a first scenario, the viewpoint is altered independently for individual image regions to avoid occlusions. In a second scenario, conventional input images are connected into a multiperspective image. In a third scenario, one or several data subsets of interest (i.e., targets) are visualized where they would be seen in the absence of occluders, as the user navigates or the targets move. The multiperspective images are rendered at interactive rates, leveraging the camera model's fast projection operation. We demonstrate the framework on terrain, urban, and molecular biology geometric datasets, as well as on volume rendered density datasets.

The State of the Art in Visual Analytics for 3D Urban Data

“…As shown in Figure 5, the browse search is the most popular type among the domain papers, which is expected given the non‐interactive (i.e., batch‐oriented) type of analyses performed in these studies, with limited exploration capabilities. This type of search is also commonly supported by distortion techniques, such as Wu et al [WP16] and Chen et al [CMF*22] (Figure 14 (Deformation)), as the user knows the location and distortion is used to enable the identification of the target. The UrbanVR visualization system presented by Zhang et al [ZZL21] is an example of how the analysis of 3D urban data can be supported by a browse search (Figure 14 (Assisted)): the user is interested in the analysis of different candidate buildings for a particular location, but needs to evaluate against certain attributes (e.g., shading and visibility).…”

“…In addition to disocclusion through scaling, Deng et al also guide users to a bird's eye perspective and demonstrate the potential of their system by encoding a 3D pollution layer [DZMQ16]. Wu and Popescu render multiple view angles from a single position and compose them to a distorted view of an urban scene [WP16]. Chen et al present a method for dynamically “exploding” urban geometry to reveal a point of interest on the ground in an AR setting [CQW17].…”

Fast occlusion-based point cloud exploration

“…Elmqvist and Tsigas [13] recognized five broad design patterns in such techniques, namely volumetric probes, multiple views, virtual X-ray, tour planners and projection distorters. In the multiple views pattern, different views and perspectives of the virtual world are presented, such as the hand-held world copy WorldIn-Miniature [36], worldlets [14], visibility widgets [30], and multi-perspective images [40]. The volumetric probes find a hidden object among occluders using a probe object, such as Depth Ray or 3D Bubble Cursor [38], possibly transforming or distorting the occluders [3,7], or rearranging cluttered objects in a planar view to select the desired one such as SQUAD [24] and EXPAND [6].…”

Exploring 3D Objects with Non-Linear Perspectives in Real-Time, a First User Study

“…Indeed, computing the rays for each pixel, instead of for each vertex, makes the triangle edges to curve, and therefore accurately fits to the expected deformation. For this first experiment, and as it is widespread in the literature, we decided to limit NLP to horizontal deformation only, like in [18,27]. Moreover, vertical bending while keeping the screen horizontal and the hands on lateral sides, is more demanding.…”